Maintenance / Repair (Mold Life Management + Prediction)
Managing Mold Life with Data, Not Experience
Accurately predict maintenance timing based on mold usage data.
01
Problem
• Mold maintenance relies on operator experience.
• Without accurate usage history, it is difficult to determine the appropriate replacement timing.
02
Limitations of
Existing Methods
• Costs increase due to premature replacement, or quality problems occur due to delayed response.
03
Solution
• Manage mold life based on mold usage data.
• Predict maintenance timing based on shot count.
04
Expected Benefits
• Unnecessary costs can be reduced and mold life can be optimized.
• Quality stability and production efficiency are improved.
Implementation Case
Before & After
Before
금형별 생산 데이터
확인 어려움
Experience-Based Maintenance
Unclear Criteria
for Regular Inspections
Excessive Replacement Costs
Reactive Response to Quality Problems
After
Usage-Based Maintenance
Mold Life Management
Based on Shot Count
Cost Optimization
Preventive Response
to Quality Problems
Implementation Case
Based on Applications at Global Manufacturing Companies
Global manufacturing companies manage mold life with data, not experience.
At global manufacturing companies, mold maintenance timing is often managed based on experience or fixed intervals.
This can result in unnecessary replacement costs or quality problems caused by missing the appropriate timing.
ShotLine supports maintenance timing management based on the actual usage data of each mold.
The number of uses and usage history are automatically recorded for each mold, enabling more systematic maintenance planning.
It can also be used to identify molds that have not been used for an extended period, helping reduce unnecessary asset operating costs.
and management gaps.